package com.dm.voicesubtitle.speech;

import com.dm.voicesubtitle.config.AppConfig;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.apache.commons.codec.binary.Base64;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import javax.sound.sampled.AudioFormat;
import java.io.IOException;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.Random;

/**
 * 语音识别类 - 使用模拟识别和简单的语言检测
 */
public class SpeechRecognizer {
    private static final Logger logger = LoggerFactory.getLogger(SpeechRecognizer.class);
    
    private final ExecutorService executorService;
    private final SpeechRecognitionListener listener;
    private final ObjectMapper objectMapper;
    private final Random random;
    private String currentLanguage;
    
    // 模拟语音识别的示例文本
    private final String[] chineseTexts = {
        "你好，这是中文语音识别测试",
        "欢迎使用语音弹幕系统",
        "今天天气很好",
        "我正在说中文",
        "语音识别功能正常工作"
    };
    
    private final String[] englishTexts = {
        "Hello, this is English speech recognition test",
        "Welcome to voice subtitle system",
        "The weather is nice today",
        "I am speaking English",
        "Speech recognition is working properly"
    };
    
    private final String[] japaneseTexts = {
        "こんにちは、これは日本語音声認識テストです",
        "音声字幕システムへようこそ",
        "今日はいい天気ですね",
        "私は日本語を話しています",
        "音声認識が正常に動作しています"
    };
    
    public SpeechRecognizer(SpeechRecognitionListener listener) {
        this.listener = listener;
        this.executorService = Executors.newFixedThreadPool(2);
        this.objectMapper = new ObjectMapper();
        this.random = new Random();
        
        // 初始化默认语言
        AppConfig.SpeechConfig config = AppConfig.getInstance().getSpeechConfig();
        this.currentLanguage = config.getDefaultLanguage();
        
        logger.info("语音识别器初始化完成，默认语言: {}", currentLanguage);
    }
    
    /**
     * 识别音频数据 - 模拟实现
     */
    public CompletableFuture<RecognitionResult> recognizeAudio(byte[] audioData, AudioFormat format) {
        return CompletableFuture.supplyAsync(() -> {
            try {
                // 模拟处理延迟
                Thread.sleep(500 + random.nextInt(1000));
                
                // 根据音频数据长度和随机因子决定是否返回结果
                if (audioData.length < 1000 || random.nextFloat() < 0.3) {
                    return null; // 模拟无识别结果
                }
                
                // 随机选择语言（模拟自动语言检测）
                String detectedLanguage = detectLanguage(audioData);
                
                // 根据检测到的语言选择相应的文本
                String transcript = getRandomTextForLanguage(detectedLanguage);
                float confidence = 0.8f + random.nextFloat() * 0.2f; // 0.8-1.0之间的置信度
                
                RecognitionResult result = new RecognitionResult(
                        transcript,
                        confidence,
                        detectedLanguage,
                        true
                );
                
                logger.debug("识别结果: {} (语言: {}, 置信度: {})", transcript, detectedLanguage, confidence);
                return result;
                
            } catch (Exception e) {
                logger.error("语音识别失败", e);
                return null;
            }
        }, executorService);
    }
    
    /**
     * 模拟语言检测
     */
    private String detectLanguage(byte[] audioData) {
        AppConfig.SpeechConfig config = AppConfig.getInstance().getSpeechConfig();
        
        if (!config.isEnableAutoLanguageDetection()) {
            return currentLanguage;
        }
        
        // 基于音频数据的简单特征进行语言检测（模拟）
        int hash = Math.abs(java.util.Arrays.hashCode(audioData));
        int languageIndex = hash % 3;
        
        switch (languageIndex) {
            case 0: return "zh-CN";
            case 1: return "en-US";
            case 2: return "ja-JP";
            default: return currentLanguage;
        }
    }
    
    /**
     * 根据语言获取随机文本
     */
    private String getRandomTextForLanguage(String languageCode) {
        String[] texts;
        
        switch (languageCode) {
            case "zh-CN":
                texts = chineseTexts;
                break;
            case "en-US":
                texts = englishTexts;
                break;
            case "ja-JP":
                texts = japaneseTexts;
                break;
            default:
                texts = chineseTexts;
                break;
        }
        
        return texts[random.nextInt(texts.length)];
    }
    
    /**
     * 同步识别音频数据
     */
    public RecognitionResult recognizeAudioSync(byte[] audioData, AudioFormat format) {
        try {
            // 模拟处理延迟
            Thread.sleep(500 + random.nextInt(1000));
            
            // 根据音频数据长度和随机因子决定是否返回结果
            if (audioData.length < 1000 || random.nextFloat() < 0.3) {
                return null; // 模拟无识别结果
            }
            
            // 随机选择语言（模拟自动语言检测）
            String detectedLanguage = detectLanguage(audioData);
            
            // 根据检测到的语言选择相应的文本
            String transcript = getRandomTextForLanguage(detectedLanguage);
            float confidence = 0.8f + random.nextFloat() * 0.2f; // 0.8-1.0之间的置信度
            
            RecognitionResult result = new RecognitionResult(
                    transcript,
                    confidence,
                    detectedLanguage,
                    true
            );
            
            logger.debug("识别结果: {} (语言: {}, 置信度: {})", transcript, detectedLanguage, confidence);
            return result;
            
        } catch (Exception e) {
            logger.error("语音识别失败", e);
            return null;
        }
    }
    
    /**
     * 流式识别（模拟实现）
     */
    public void startStreamingRecognition() {
        logger.info("开始流式语音识别（模拟模式）");
        // 在实际应用中，这里会启动实时流式识别
        // 目前使用音频数据驱动的方式
    }
    
    /**
     * 设置识别语言
     */
    public void setLanguage(String languageCode) {
        this.currentLanguage = languageCode;
        AppConfig.SpeechConfig config = AppConfig.getInstance().getSpeechConfig();
        config.setDefaultLanguage(languageCode);
        logger.info("识别语言已设置为: {}", languageCode);
    }
    
    /**
     * 关闭资源
     */
    public void close() {
        if (executorService != null) {
            executorService.shutdown();
        }
        logger.info("语音识别器已关闭");
    }
    
    /**
     * 识别结果类
     */
    public static class RecognitionResult {
        private final String transcript;
        private final float confidence;
        private final String languageCode;
        private final boolean isFinal;
        
        public RecognitionResult(String transcript, float confidence, String languageCode, boolean isFinal) {
            this.transcript = transcript;
            this.confidence = confidence;
            this.languageCode = languageCode;
            this.isFinal = isFinal;
        }
        
        // Getter方法
        public String getTranscript() { return transcript; }
        public float getConfidence() { return confidence; }
        public String getLanguageCode() { return languageCode; }
        public boolean isFinal() { return isFinal; }
        
        @Override
        public String toString() {
            return "RecognitionResult{" +
                    "transcript='" + transcript + '\'' +
                    ", confidence=" + confidence +
                    ", languageCode='" + languageCode + '\'' +
                    ", isFinal=" + isFinal +
                    '}';
        }
    }
    
    /**
     * 语音识别监听器接口
     */
    public interface SpeechRecognitionListener {
        void onRecognitionResult(RecognitionResult result);
        void onError(Throwable error);
    }
} 